library(tidyverse)
## -- Attaching packages -------------------------------- tidyverse 1.3.0 --
## v ggplot2 3.2.1 v purrr 0.3.3
## v tibble 2.1.3 v dplyr 0.8.4
## v tidyr 1.0.2 v stringr 1.4.0
## v readr 1.3.1 v forcats 0.4.0
## -- Conflicts ----------------------------------- tidyverse_conflicts() --
## x dplyr::filter() masks stats::filter()
## x dplyr::lag() masks stats::lag()
library(nycflights13)
## Warning: package 'nycflights13' was built under R version 3.6.3
Quais são os nomes das variáveis?
names(flights)
## [1] "year" "month" "day" "dep_time"
## [5] "sched_dep_time" "dep_delay" "arr_time" "sched_arr_time"
## [9] "arr_delay" "carrier" "flight" "tailnum"
## [13] "origin" "dest" "air_time" "distance"
## [17] "hour" "minute" "time_hour"
Renomear a variável arr_time
flights %>% rename(arrival_time = arr_time)
flights
flights_renomeado <- flights %>% rename(arrival_time = arr_time)
flights_renomeado
flights2 <- flights %>% rename(arrival_time = arr_time) %>%
rename(departure_time = dep_time)
flights
flights3 <- flights %>% rename(arrival_time = arr_time,
departure_time = dep_time)
flights3
flights %>% select(year, month, day)
flights4 <- flights %>% select(year, month, day)
flights4
flights5 <- flights %>% mutate(dep_delay_dobro = dep_delay*2)
flights5
flights %>% mutate(calculo_metade_diferenca = (arr_time - dep_time)/2 )
flights %>% mutate(dep_delay = dep_delay * 60)
flights %>% mutate(origin = tolower(origin))
flights %>% slice(5)
flights %>% slice(1:5)
linhas_desejadas <- c(1, 4, 5, 6, 22, 169)
flights %>% slice(linhas_desejadas)
flights %>% slice(-1)
flights %>% slice(10:20)
flights %>% slice(seq(from = 1, to = 100, by = 10))
seq(from = 1, to = 100, by = 10)
## [1] 1 11 21 31 41 51 61 71 81 91
flights %>% slice(seq(1, 100, 10))
# ?seq
flights_junho <- flights %>% filter(month == 6)
flights_junho
42 == 41 # FALSE
## [1] FALSE
42 != 41 # TRUE
## [1] TRUE
(2 + 2) == (3 + 1) # TRUE
## [1] TRUE
(2 + 2) != (3 + 1) # FALSE
## [1] FALSE
5 > 3 # TRUE
## [1] TRUE
5 < 3 # FALSE
## [1] FALSE
42 > 42 # FALSE
## [1] FALSE
42 < 41 # FALSE
## [1] FALSE
42 >= 42 # TRUE
## [1] TRUE
42 <= 41 # FALSE
## [1] FALSE
"texto" == "texto" # TRUE
## [1] TRUE
"texto" == "texTo" # FALSE
## [1] FALSE
"texto" != "texto" # FALSE
## [1] FALSE
"a" > "b" # FALSE
## [1] FALSE
"a" < "b" # TRUE
## [1] TRUE
"A" < "b" # TRUE
## [1] TRUE
"A" > "a" # TRUE - Surpresa - o maiúsculo é considerado maior que a mesma letra minúscula
## [1] TRUE
TRUE == 1 # TRUE
## [1] TRUE
FALSE == 0 # TRUE
## [1] TRUE
TRUE > FALSE # TRUE
## [1] TRUE
x <- 5
y <- 10
x > y #FALSE
## [1] FALSE
flights %>% filter(month == 6 & day == 5)
flights %>% filter(month == 6 & day == 5 & dep_time < 1200)
flights %>% filter((dep_time <= 500 |
dest == "ATL") & arr_delay >= 50)
flights %>% filter(dep_time <= 500 |
dest == "ATL"
& arr_delay >= 50)
flights %>% filter(!((dep_time <= 500 |
dest == "ATL") & arr_delay >= 50))
flights %>%
rename(arrival_time = arr_time) %>%
mutate(dep_delay = dep_delay * 60) %>%
filter(month == 6 & day == 5) %>%
select(year, month, day, arrival_time, dep_delay)
rstudioapi::navigateToFile("aula_2_exercicios.Rmd")
file1 <- "https://raw.githubusercontent.com/leobarone/ifch_intro_r/master/data/bf_amostra_hv.csv"
dados <- read_csv(file1)
## Parsed with column specification:
## cols(
## uf = col_character(),
## codmunic = col_double(),
## munic = col_character(),
## nis = col_double(),
## valor = col_double()
## )
dados <- read_delim(file1,
delim = ",")
## Parsed with column specification:
## cols(
## uf = col_character(),
## codmunic = col_double(),
## munic = col_character(),
## nis = col_double(),
## valor = col_double()
## )
file_semi_colon <-
"https://raw.githubusercontent.com/leobarone/ifch_intro_r/master/data/bf_amostra_hp.csv"
dados <- read_delim(file_semi_colon,
delim = ";")
## Parsed with column specification:
## cols(
## uf = col_character(),
## codmunic = col_double(),
## munic = col_character(),
## nis = col_double(),
## valor = col_double()
## )
file_tab <-
"https://raw.githubusercontent.com/leobarone/ifch_intro_r/master/data/bf_amostra_ht.csv"
dados <- read_delim(file_tab,
delim = "\t")
## Parsed with column specification:
## cols(
## uf = col_character(),
## codmunic = col_double(),
## munic = col_character(),
## nis = col_double(),
## valor = col_double()
## )
file_sem_header <-
"https://raw.githubusercontent.com/leobarone/ifch_intro_r/master/data/bf_amostra_nv.csv"
dados <- read_delim(file_sem_header,
col_names = F,
delim = ",")
## Parsed with column specification:
## cols(
## X1 = col_character(),
## X2 = col_double(),
## X3 = col_character(),
## X4 = col_double(),
## X5 = col_double()
## )
dados <- read_delim(
file_sem_header,
col_names = c(
"estado",
"municipio_cod",
"municipio_nome",
"NIS",
"transferido"
),
delim = ","
)
## Parsed with column specification:
## cols(
## estado = col_character(),
## municipio_cod = col_double(),
## municipio_nome = col_character(),
## NIS = col_double(),
## transferido = col_double()
## )
dados <- read_delim(file1,
delim = ",",
col_types = "cicid")
dados <- read_csv(file1)
## Parsed with column specification:
## cols(
## uf = col_character(),
## codmunic = col_double(),
## munic = col_character(),
## nis = col_double(),
## valor = col_double()
## )
dados <- read_delim(file1,
delim = ",",
locale = locale(decimal_mark = ",", grouping_mark =
"."))
## Parsed with column specification:
## cols(
## uf = col_character(),
## codmunic = col_double(),
## munic = col_character(),
## nis = col_double(),
## valor = col_double()
## )
dados <- read_delim(file1,
delim = ",",
locale = locale(encoding = 'latin1'))
## Parsed with column specification:
## cols(
## uf = col_character(),
## codmunic = col_double(),
## munic = col_character(),
## nis = col_double(),
## valor = col_double()
## )
library("readxl")
library(readxl)
url <- "ftp://ftp.ibge.gov.br/Perfil_Municipios/2005/base_MUNIC_2005.zip"
destfile <- "dados/base_MUNIC_2005.zip"
curl::curl_download(url, destfile)
utils::unzip(destfile)
excel_sheets("dados/Base 2005.xls")
## [1] "Dicionário" "Informações prefeito" "Adm Direta"
## [4] "Adm Indireta" "Leg e inst planej" "Recursos gestão"
## [7] "Articulações inter" "Habitação" "Transporte"
## [10] "Cultura" "Variáveis externas"
externas <- read_excel("dados/Base 2005.xls", "Variáveis externas")
externas <- read_excel("dados/Base 2005.xls", 11)
head(externas)
library("haven")
latino_barometro_spss <- read_spss("dados/F00004529-Latinobarometro_2015_sav/Latinobarometro_2015_Eng.sav")
latino_barometro_stata <- read_stata("dados/F00004530-Latinobarometro_2015_dta/Latinobarometro_2015_Eng.dta")